Intern, Demand Impact Modeling

Employment Type

Internship

6 months

You will work as an integral member of the Industry Analysis team within the Sustainability and Economics Division, performing research regarding the empirical price impact on air travel demand. Your work will include supporting a research project that estimates demand elasticities at various granularity levels, using IATA’s unique air travel demand and price data, and contribute across all stages of the research cycle—from literature review and data preparation to econometric modeling, robustness testing, and final documentation.

• Conduct a structured literature review spanning transport, energy, trade, and tourism economics to compare price elasticity estimation methods, instrument validity, and demand modeling best practices.
• Estimate price elasticities of air travel demand at various levels using basic panel econometric methods (e.g., OLS, fixed effects) within an established econometric modeling framework.
• Design and implement robustness and sensitivity checks, sub-sample analysis, and model diagnostics to stress‑test key elasticity estimates.
• Produce well‑documented, reproducible code in R hosted on Bitbucket, and write clear analytical memos and a final project report summarizing methodology, results, and limitations.
• Present interim findings to the project team, contribute to internal knowledge‑sharing, and support the preparation of results for external publication or stakeholder communication.

• Master’s degree in Economics, Econometrics, Transport Economics, or a closely related quantitative field; candidates with a background in transport modeling with experience in researching price elasticities are particularly encouraged.
• Demonstrated ability to conduct high‑quality research independently, with a systematic approach to reviewing academic literature with critical thinking.
• Good understanding of econometrics and causal inference, ideally regarding panel data methods (fixed effects, first differences), instrumental variables, and an understanding of simultaneity and endogeneity in demand estimation.
• Experience in working with large‑scale panel datasets and in data engineering using R is a strong advantage.
• Familiarity with version control via Git Hub or Bitbucket and a commitment to reproducible research workflows is highly preferred.
• Excellent written and spoken English, with the ability to communicate technical findings clearly to both specialist and non‑specialist audiences; additional languages are an advantage.
• Capacity for independent, creative thinking in a research environment; able to take ownership of analytical tasks, identify methodological challenges, and propose solutions with limited supervision.
• Strong interpersonal skills and a good team player.

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